Language network measures at rest indicate individual differences in naming decline after anterior temporal lobe resection

Abstract

While anterior temporal lobe (ATL) resection is an effective treatment for temporal lobe epilepsy, surgery on the dominant hemisphere is associated with variable decline in confrontation naming. Accurate prediction of naming impairment is critical to inform clinical decision making, and while there has been some degree of success using task-based functional MRI (fMRI) paradigms, there remains a growing interest in the predictive utility of resting-state connectivity as it allows for relatively shorter scans with low task demands. Our objective was to assess the relationship between measures of preoperative resting-state connectivity and postoperative naming change in patients following left ATL resection. We compared the resting language network connectivity of each patient to a normative healthy control template using a novel measure called "matrix similarity," and found that patients with more abnormal global language-network connectivity-particularly of regions spared from surgery-showed greater postoperative naming decline than those with normative patterns of connectivity. When we interrogated the degree centrality of to-be-resected regions in a more targeted approach of the pathological temporal lobe, we found that greater functional integration of those regions with the rest of the language network at rest was related to greater decline in naming following surgery. Finally, we found that matrix similarity was a better predictor of postoperative outcome than degree within to-be-resected regions, network clustering, modularity, and language task fMRI laterality. We provide some of the first evidence that using this novel measure, a relatively short preoperative resting scan can be exploited to inform naming ability following ATL resection.

Language lateralization from task‐based and resting state functional MRI in patients with epilepsy

“…Clinical applications of resting state fMRI to epilepsy surgery include preoperative functional mapping to help guide surgical planning (Doucet, Pustina, et al, 2015; Liu et al, 2009; Mitchell, Hacker, & Breshears, 2013) and identifying prognostic markers of individual patients' relevant clinical outcomes after surgery (Boerwinkle, Mohanty, Foldes, et al, 2017; He et al, 2017; Negishi, Martuzzi, Novotny, Spencer, & Constable, 2011). There are limited data on the ability of resting state fMRI to predict neurocognitive outcomes after surgery, including language and memory (Audrain, Barnett, & McAndrews, 2018; Doucet, Rider, & Taylor, 2015; McCormick, Quraan, Cohn, Valiante, & McAndrews, 2013). In addition, others have shown that the best predictive model of verbal fluency change following dominant anterior temporal lobectomy was one that combined all three imaging modalities: task fMRI, resting state fMRI, and DTI (Osipowicz, Sperling, Sharan, & Tracy, 2016).…”

Language Dominance in Patients With Malformations of Cortical Development and Epilepsy

“…In this study, we tested solely an expressive component of the language by utilizing the word generation paradigm, which has also been used by other groups for determining language networks in epilepsy patients (28). Paradigms related to semantic aspects of language, such as picture/auditory naming or semantic decision tasks are also widely used (31, 32, 42–45). Different fMRI tasks, which engage diverse aspects of language, may show either equal or various lateralization patterns (28, 31, 32, 42–45).…”

“…Paradigms related to semantic aspects of language, such as picture/auditory naming or semantic decision tasks are also widely used (31, 32, 42–45). Different fMRI tasks, which engage diverse aspects of language, may show either equal or various lateralization patterns (28, 31, 32, 42–45). They may also have different predictive value for postoperative naming decline in epilepsy surgery patients.…”

Emerging Trends in Neuroimaging of Epilepsy

“… 44 , 45 Other recent work has shown the ability of preoperative resting state fMRI and white matter connectome markers to predict postoperative cognition, particularly in relation to language. 46 …”